Dontopedia

angry

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)

angry has 14 facts recorded in Dontopedia across 7 references, with 2 live disagreements.

14 facts·5 predicates·7 sources·2 in dispute

Mostly:rdf:type(7), semantic category(2), is member of(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (11)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

containsContains(6)

containsElementContains Element(1)

containsEmotionTermContains Emotion Term(1)

containsExactContains Exact(1)

elementElement(1)

processesTermsProcesses Terms(1)

Other facts (12)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

12 facts
PredicateValueRef
Rdf:typeEmotional Tone[1]
Rdf:typeEmotion[2]
Rdf:typeWord[3]
Rdf:typeString[4]
Rdf:typeTerm[5]
Rdf:typeString Literal[6]
Rdf:typeTest Term[7]
Semantic CategoryEmotion[5]
Semantic CategoryNegative Emotion[6]
Is Member ofWords Variable[4]
Member ofTerms[6]
Semantic FieldEmotion[6]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

14 undated
—
labelblah/agents/5
angry
—
typeblah/agents/5
ex:EmotionalTone
—
typebeam/26375e84-be0b-411d-8740-b19721f3bf80
ex:Emotion
—
typebeam/fdf83faa-03c9-4e80-9792-6fa66000e80d
ex:Word
—
typebeam/534be9d2-c97a-4867-8efb-8f090879be4b
ex:String
—
labelbeam/534be9d2-c97a-4867-8efb-8f090879be4b
angry
—
isMemberOfbeam/534be9d2-c97a-4867-8efb-8f090879be4b
ex:words-variable
—
typebeam/add559bf-3ce5-4390-a544-0660ac8acf99
ex:Term
—
semanticCategorybeam/add559bf-3ce5-4390-a544-0660ac8acf99
ex:emotion
—
typebeam/f0cc860e-7f75-4530-abef-84dc82b5e5ad
ex:StringLiteral
—
memberOfbeam/f0cc860e-7f75-4530-abef-84dc82b5e5ad
ex:terms
—
semanticCategorybeam/f0cc860e-7f75-4530-abef-84dc82b5e5ad
ex:negative_emotion
—
semanticFieldbeam/f0cc860e-7f75-4530-abef-84dc82b5e5ad
ex:emotion
—
typebeam/5e1fccc0-109f-4d58-b6c4-6482a168aad7
ex:TestTerm

References (7)

7 references
  1. [1]52 facts
    ctx:discord/blah/agents/5
    • full textctx:discord/blah/agents/5
      text/plain2 KBdoc:discord/blah/agents/5
      Show excerpt
      [2026-02-18 10:45] lisamegawatts: teams be teams everywhere you go, i loved this back and forth between ml team and dev team (files: image.png) [2026-02-19 18:06] traves_theberge: (files: HBhXt3aW4AEz7wV.png) [2026-02-19 19:47] traves_theb…
  2. [2]26375e84 Be0b 411d 8740 B19721f3bf801 fact
    ctx:claims/beam/26375e84-be0b-411d-8740-b19721f3bf80
    • full textbeam-chunk
      text/plain1 KBdoc:beam/26375e84-be0b-411d-8740-b19721f3bf80
      Show excerpt
      4. **Visualizations**: Use visualizations to help identify patterns and outliers in the data. ### Detailed Logging Enhance your logging to capture more details about each lookup: ```python import logging import time logging.basicConfig(…
  3. [3]Fdf83faa 03c9 4e80 9792 6fa66000e80d1 fact
    ctx:claims/beam/fdf83faa-03c9-4e80-9792-6fa66000e80d
    • full textbeam-chunk
      text/plain1 KBdoc:beam/fdf83faa-03c9-4e80-9792-6fa66000e80d
      Show excerpt
      logging.basicConfig(level=logging.INFO) def thesaurus_lookup(word): start_time = time.time() # Simulate the lookup time.sleep(0.1) end_time = time.time() logging.info(f"Lookup took {end_time - start_time} seconds") …
  4. [4]534be9d2 C97a 4867 8efb 8f090879be4b3 facts
    ctx:claims/beam/534be9d2-c97a-4867-8efb-8f090879be4b
    • full textbeam-chunk
      text/plain1 KBdoc:beam/534be9d2-c97a-4867-8efb-8f090879be4b
      Show excerpt
      logging.info(f"Thesaurus lookup for '{word}' took {end_time - start_time:.6f} seconds") return ["synonym1", "synonym2"] # Test the lookup words = ["happy", "sad", "angry"] * 100 # Simulate a larger dataset for word in words: …
  5. [5]Add559bf 3ce5 4390 A544 0660ac8acf992 facts
    ctx:claims/beam/add559bf-3ce5-4390-a544-0660ac8acf99
    • full textbeam-chunk
      text/plain1 KBdoc:beam/add559bf-3ce5-4390-a544-0660ac8acf99
      Show excerpt
      closest_synonyms.extend([synonyms[i] for i in np.argsort(similarities)[-2:]]) # Take top 2 closest synonyms return closest_synonyms # Test the synonym expansion terms = ["happy", "sad", "angry"] for term in terms: synonym…
  6. [6]F0cc860e 7f75 4530 Abef 84dc82b5e5ad4 facts
    ctx:claims/beam/f0cc860e-7f75-4530-abef-84dc82b5e5ad
    • full textbeam-chunk
      text/plain1 KBdoc:beam/f0cc860e-7f75-4530-abef-84dc82b5e5ad
      Show excerpt
      term_embedding = get_contextual_embeddings(term) closest_synonyms = [] for word, synonyms in thesaurus.items(): word_embedding = get_contextual_embeddings(word) similarities = [np.dot(term_embedding, get_context…
  7. [7]5e1fccc0 109f 4d58 B6c4 6482a168aad71 fact
    ctx:claims/beam/5e1fccc0-109f-4d58-b6c4-6482a168aad7
    • full textbeam-chunk
      text/plain1 KBdoc:beam/5e1fccc0-109f-4d58-b6c4-6482a168aad7
      Show excerpt
      for word, synonyms in thesaurus.items(): word_embedding = get_contextual_embeddings(word) similarities = [np.dot(term_embedding, get_contextual_embeddings(syn)) for syn in synonyms] closest_synonyms.extend([synon…

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